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f_next = self._obj['next_event'] == event_order[1]
s_next = self._obj[f_cur & f_next].copy()
s_cur = self._obj[f_cur & (~f_next)].copy()
s_cur.time_diff[s_cur.time_diff < limit].hist(alpha=0.5, log=True,
bins=bins, label='Others {:.2f}'.format(
(s_cur.time_diff < limit).sum() / f_cur.sum()
))
s_next.time_diff[s_next.time_diff < limit].hist(alpha=0.7, log=True,
bins=bins,
label='Selected event order {:.2f}'.format(
(s_next.time_diff < limit).sum() / f_cur.sum()
))
plot.sns.mpl.pyplot.legend()
plot.sns.mpl.pyplot.show()
(s_cur.next_event.value_counts() / f_cur.sum()).iloc[:topk].plot.bar()